Abstract: A non-transitory computer readable medium stores at least one database (12) storing an index of training resources (14); and instructions readable and executable by at least one electronic processor (12) to perform a training session generation method (100) includes receiving requests for training from a plurality of medical professionals; obtaining information related to the medical professionals of the plurality of medical professionals; and determining a training session using training resources indexed in the at least one database including determining at least two of the medical professionals to invite to participate in the training session based on the received requests and the obtained information.

Abstract: At least one database stores reference content. In an annotation method, an annotation to an item of the reference content is received via a user interface, an annotation context of the annotation is determined at least based on analysis of content of the annotation, and the item of the reference content is updated in the database with the annotation tagged with the annotation context. In a reference content presentation method, an item of the reference content is presented via the user interface, a presentation context of the presenting is determined, and it is determined whether a comparison of the annotation context and the presentation context satisfies a sharing filter. In response to the sharing filter being satisfied, the annotation is presented via the user interface. The annotation is not presented if the sharing filter is not satisfied.

Abstract: A mechanism for generating a partially denoised image. A residual noise image, obtained by processing an image using a convolutional neural network, is weighted. The blending or combination of the weighted residual noise image and the (original) image generates the partially denoised image.

Abstract: A non-transitory computer readable medium stores at least one database (30) storing clinical competency framework profiles (32) for clinical competencies for a plurality of clinicians at a plurality of medical facilities; and instructions readable and executable by at least one electronic processor (16) to perform a learning activities recommendation method (100) comprising: linking educational content units (38) completed by clinicians to clinical competencies of the clinical competency framework profiles that are fulfilled by the completed learning activities; correlating clinical competency frameworks of different medical facilities that are for the same or similar clinical competencies in the clinical competency framework profiles; and recommending one or more of the educational content units to a clinician seeking to fulfill a clinical competency in one clinical competency framework based on the correlated clinical competency frameworks and the linked educational content units.

Abstract: A method for use in image reconstruction of CT projection data, which aims at reducing motion artefacts in reconstructed images caused by movement of anatomical bodies. Embodiments are based on mitigating motion artefacts based on restricting the range of data that is used for reconstructing each slice. More particularly, a sub-range of the projection data corresponding to each slice is selected, this sub-range being chosen based on determining one or more sub-windows of visibility of a target anatomical object or event within the projection data sequence. The event may be a particular phase of a movement cycle of the anatomical body. The structure could be a particular portion of the anatomical body which is of interest. Either approach leads to reduction of motion artefacts within a single slice, by restricting the data range, and focusing upon the data which is most relevant clinically.

Abstract: One embodiment of the present disclosure may provide a method for training and tuning a neural network model, including: adding simulated noise to an initial image of an object to generate a noisy image (601, 603), the simulated noise taking the same form as natural noise in the initial image; training a neural network model on the noisy image using the initial image as ground truth (605), wherein in the neural network model is trained on the noisy work model a tuning variable is extracted or generated, the tuning variable defining an amount of noise removed during use (607); identifying a first value for the tuning variable that minimizes a training cost function for the tuning variable is identified or for the initial image; and assigning a second value for the tuning variable (611), the second value different than the first value, wherein the neural network model identifies more noise in the noisy image when using the second value than when using the first value.

Abstract: The present invention relates to an apparatus (10) for correcting computer tomography (“CT”) X-ray data acquired at high relative pitch, the apparatus comprising: an input unit (20); a processing unit (30); and an output unit (40). The input unit is configured to provide the processing unit with CT X-ray data of a body part of a person acquired at high relative pitch. The processing unit is configured to determine CT slice reconstruction data of the body part of the person with no or reduced high relative pitch operation reconstruction artefacts using a machine learning algorithm. The machine learning algorithm was trained on the basis of CT slice reconstruction data, and wherein the CT slice reconstruction data comprised first CT slice reconstruction data with high relative pitch reconstruction artefacts and comprised second CT slice reconstruction data with less, less severe, or no high relative pitch reconstruction artefacts.

Abstract: An imaging system (MIS), optionally a medical imaging system, with wireless communication capability and related method. The imaging system comprises a gantry (RG) rotatable around a rotation axis. The gantry includes a detector device (D) capable of recording, in plural spatial positions, measurement data in relation to a subject (such as a patient) (PAT) to be imaged. The system also includes a radio transmitter (TX) for generating a directed radio beam propagatable along a propagation axis to transmit the measurement data to a radio receiver (RX). The radio transmitter (TX) is arranged at the rotatable gantry and is operable so that the propagation direction intersects the rotation axis in a location that is situated away from the rotatable gantry.

Abstract: In a method and system for reconstructing computed tomography image data in which CT image data is de-noised. Then simulated noise is added, followed by another de-noising step to estimate the bias. Then, the estimated bias information is used to correct the original de-noised image data to arrive at second pass image data.

Abstract: In a method and system for reconstructing computed tomography image data in which CT image data is de-noised. Then simulated noise is added, followed by another de-noising step to estimate the bias. Then, the estimated bias information is used to correct the original de-noised image data to arrive at second pass image data.

Abstract: An imaging system (400) includes a radiation source (408) configured to emit X-ray radiation, a detector array (410) configured to detected X-ray radiation and generate projection data indicative thereof, and a first processing chain (418) configured to reconstruct the projection data and generate a noise only image. A method includes receiving projection data produced by an imaging system and processing the projection data with a first processing chain configured to reconstruct the projection data and generate a noise only image. A processor is configured to: scan an object or subject with an x-ray imaging system and generating projection data, process the projection data with a first processing chain configured to reconstruct the projection data and generate a noise only image, process the projection data with a second processing chain configured to reconstruct the projection data and generate a structure image, and de-noise the structure image based on the noise only image.

Abstract: The present invention relates to a photon scanning apparatus comprising a photon source (2) to emit a photon beam (4), a photon detector (6) to detect photons emitted from the photon source (2). The photon source (2) is adapted to emit the photon beam (4) in accordance with a predetermined pulse width modulation scheme at a predetermined flux rate, wherein the pulse width modulation scheme defines pulse widths of the photon beam (4) for respective positions of the photon source (2) and the photon detector around a central axis (R) and an object to be scanned. The photon detector (6) is adapted to start detecting photons with a delay relative to the photon source starting to emit photons and to finish detecting photons prior to the photon source stopping to emit photons. The photon scanning apparatus thus only has to be calibrated for the predetermined flux rate.

Abstract: The present invention relates to an apparatus for tomosynthesis image reconstruction. It is described to provide (210) a first projection image data set and a second projection image data set acquired after acquisition of the first projection image data set, wherein, the first projection image data set comprises first projection data, and the second projection image data set comprises second projection data, and wherein the first projection image data set is useable for the reconstruction of a tomosynthesis image of at least a region of interest of a body part and wherein the second projection image data set is useable for the reconstruction of a tomosynthesis image of at least the region of interest of the body part. A subset of the first projection data is selected (220).

Abstract: The present invention relates to a device (100) for denoising a vector-valued image, the device (100) comprising: a generator (10), which is configured to generate an initial loss function (L_I) comprising at least one initial covariance matrix (ICM) defining a model of correlated noise for each pixel of the vector-valued image; a processor (20), which is configured to provide a final loss function (L_F) comprising a set of at least one final covariance matrix (FCM) based on the initial loss function by modifying at least one submatrix and/or at least one matrix element of the initial covariance matrix (ICM); and a noise-suppressor (30), which is configured to denoise the vector-valued image using the final loss function (L_F) comprising the set of the at least one final covariance matrix (FCM).

Abstract: An image processing apparatus (IP) comprising an input port (IN) for receiving projection data through respective 3D locations in an imaging region, said projection date collected in a scan operation by an imaging apparatus (IM). An image segment generator (IGS) of said apparatus (IP) is configured to generate, based on said projection data, a first image segment for said 3D locations. A visualizer (VIZ) configured to effect displaying said first image segment on a display device before or whilst the image apparatus collects projection data for a different 3D location.

Abstract: The present invention relates to a photon scanning apparatus comprising a photon source (2) to emit a photon beam (4), a photon detector (6) to detect photons emitted from the photon source (2). The photon source (2) is adapted to emit the photon beam (4) in accordance with a predetermined pulse width modulation scheme at a predetermined flux rate, wherein the pulse width modulation scheme defines pulse widths of the photon beam (4) for respective positions of the photon source (2) and the photon detector around a central axis (R) and an object to be scanned. The photon detector (6) is adapted to start detecting photons with a delay relative to the photon source starting to emit photons and to finish detecting photons prior to the photon source stopping to emit photons. The photon scanning apparatus thus only has to be calibrated for the predetermined flux rate.

Abstract: The present invention relates to a device for reconstructing an X-ray tomography image, the device comprising a reconstruction module, which is configured to utilize an ordered subset maximum likelihood optimization with a diagonal paraboloid approximation of a cost function for the reconstructing of the X-ray tomography image; and a calculation module, which is configured to calculate a pre-computable denominator term for the cost function for a plurality of subsets of projection data based on a distribution of diagonal denominator terms over the plurality of the subsets of the projection data.

Abstract: The present invention relates to an image reconstruction system for statistically reconstructing images from transmission measurements. The image reconstruction system comprises an update equation providing unit for providing an update equation based on an iterative statistical model. The update equation comprises a data term and a regularization term. The invention proposes to not modify the regularization term, but rather the weights with which individual measurements contribute are modified on a per image voxel and per measurement basis. This is achieved by modifying the contributions of each measurement by including an additional weight on a per image voxel/per measurement basis. The additional weight for each measurement is determined by calculating the noise perpendicular to each measurement ray at each voxel position and a voxel and measurement dependent weight for each measurement, and integrated into the update equation's data term.

Abstract: An imaging system (400) includes a radiation source (408) configured to emit X-ray radiation, a detector array (410) configured to detected X-ray radiation and generate projection data indicative thereof, and a first processing chain (418) configured to reconstruct the projection data and generate a noise only image. A method includes receiving projection data produced by an imaging system and processing the projection data with a first processing chain configured to reconstruct the projection data and generate a noise only image. A processor is configured to: scan an object or subject with an x-ray imaging system and generating projection data, process the projection data with a first processing chain configured to reconstruct the projection data and generate a noise only image, process the projection data with a second processing chain configured to reconstruct the projection data and generate a structure image, and de-noise the structure image based on the noise only image.

Abstract: The present invention relates to an apparatus for tomosynthesis image reconstruction. It is described to provide (210) a first projection image data set and a second projection image data set acquired after acquisition of the first projection image data set, wherein, the first projection image data set comprises first projection data, and the second projection image data set comprises second projection data, and wherein the first projection image data set is useable for the reconstruction of a tomosynthesis image of at least a region of interest of a body part and wherein the second projection image data set is useable for the reconstruction of a tomosynthesis image of at least the region of interest of the body part. A subset of the first projection data is selected (220).